Opening the Black Box: Using Emerging Data from the Early Elementary Grades to Inform Decision-Making
Herring, Walter, Education - School of Education and Human Development, University of Virginia
Bassok, Daphna, CU-Leadshp Fndns & Pol Studies, University of Virginia
While the early elementary grades (grades K through 2) are critically important to children’s academic development, education policy in the United States tends to shift stakeholders’ focus away from grades K through 2. The Every Student Succeeds Act (ESSA), for example, requires that states administer standardized tests in math and reading beginning in third grade and holds schools accountable for students’ performance on those assessments. The availability of standardized testing data in third grade and beyond has allowed policymakers and researchers to explore important questions pertaining to children’s learning in the upper elementary and middle grades. By contrast, stakeholders have traditionally not had access to the systemwide academic data needed to explore such questions in the early elementary grades at the state and local levels.
In recent years, lawmakers have invested considerably in efforts to collect data regarding children’s academic skills in the early grades. For example, a growing number of states now administer kindergarten entry assessments (KEAs) and other formative assessments in grades K through 2. These emerging data sources give stakeholders an opportunity to inform their decision-making in new ways, but to date relatively few studies have used them to explore policy-relevant questions in the early elementary grades.
This dissertation fills this gap by highlighting how stakeholders can leverage data from grades K through 2 to inform policy discussions. In the first chapter, my coauthors and I use data from a KEA in Virginia to identify disparities along lines of race and socioeconomic status in the relationship between children’s early literacy skills and their future reading outcomes. Our findings reveal important inequities in children’s opportunities to learn in the early elementary grades. In the second chapter, I explore how these same data could be used to improve efforts to address these inequities by more accurately identifying children in need of literacy intervention. I show that using widely available data from KEAs and other sources could help policymakers identify hundreds of additional kindergarteners who will go on to fall below reading proficiency standards in third grade each year.
These first two chapters focus on how policymakers can use data from the early grades to inform their decision-making, but in practice stakeholders continue to rely on students’ test scores in third grade and beyond when making decisions. Schools’ accountability ratings under ESSA, for instance, are largely determined by students’ test scores in grades 3 and above and do not directly account for students’ learning in the early elementary grades. As such, the ratings that schools receive under ESSA might not be representative of the academic outcomes of children in grades K through 2 and could send an incomplete or misleading signal to parents, policymakers, and other stakeholders who rely on these measures of school quality to make decisions. In my third chapter, I use early assessment data to shed light on this issue and find that the decisions that stakeholders make based on school ratings could change considerably if these ratings included measures of children’s academic progress in grades K through 2.
Together, these three chapters provide new insight regarding how stakeholders can leverage increasingly available data in grades K through 2. I demonstrate how these data can be used to inform decision-making and discuss the need to continue to track children’s learning in the critically important early elementary grades.
PHD (Doctor of Philosophy)
Early elementary grades, Educational inequity, Predictive analytics, Literacy, Accountability
Institute of Education Sciences (R305B200005)